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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
Yes, AI excels at data standardization and error correction, making these capabilities accessible through simple conversation. This technology transforms chaotic business system exports into clean, standardized datasets ready for analysis without complex formulas or manual corrections.
Here’s how AI solves common data quality challenges that plague spreadsheet reports from CRM systems, databases, and other business applications.
Standardize and clean business system data using AI-powered automation with Coefficient
Coefficient’s AI Sheets Assistant makes data standardization accessible through natural language commands. Instead of writing complex REGEX patterns or formulas, you simply describe the format you want and the AI handles the transformation across thousands of records.
This approach works with live data from HubSpot , Salesforce, databases, and other business systems, ensuring your analysis starts with clean, consistent information.
How to make it work
Step 1. Connect your business system and analyze data quality.
Use Coefficient to pull live data from HubSpot, Salesforce, or databases directly into Google Sheets. Ask the AI to “Show me all data inconsistencies in this dataset” to identify standardization opportunities and common errors across your records.
Step 2. Apply intelligent standardization rules.
Use commands like “Standardize all company names to their common form” to handle variations like “IBM,” “I.B.M.,” and “International Business Machines.” The AI understands context and applies consistent formatting across name fields, addresses, phone numbers, and other text data.
Step 3. Detect and correct logical errors automatically.
Tell the AI to “Find deals where close date is before creation date” or “Identify contacts with invalid email formats.” The system catches errors that manual review often misses and suggests corrections based on data patterns and business logic.
Step 4. Set up automated workflows for ongoing data quality.
Create bulk transformation workflows that trim whitespace, remove special characters, standardize phone formats, and convert currency—all applied automatically to new data. Schedule these rules to run with each data refresh, maintaining quality continuously.
Transform messy exports into analysis-ready datasets in seconds
AI-powered standardization eliminates the hours typically spent preparing data for analysis. Teams report 40% improvement in territory assignment accuracy, 25% increase in campaign delivery rates, and 90% reduction in fulfillment errors after implementing automated data hygiene. Start cleaning your business system data with intelligent automation.
